A. I. J. M. van Dijk

Rainfall intensity–kinetic energy relationships: a critical literature appraisal

Abstract Knowledge of the relationship between rainfall intensity and kinetic energy and its variations in time and space is important for erosion prediction. However, between studies considerable variations exist in the reported shape and coefficients of this relationship. Some differences can be explained by methods of measurement and interpretation and sample size, range and bias, while part of the variability corresponds to actual differences in rainfall generating mechanisms. The present paper critically reviews published studies of rainfall intensity and kinetic energy with a view to derive a general predictive equation of an exponential form. The performance of this general equation is compared to that of existing equations using measured rainfall intensity and kinetic energy data for a site in southeastern Australia. It appeared that the energy of individual storms could only be predicted with limited accuracy because of natural variations in rainfall characteristics. By and large, the general equation produced energy estimates that were within 10% of predictions by a range of parameterisations of the exponential model fitted to specific data-sets. Re-calculation of rainfall erosivity factors as obtained by the older and revised USLE approaches does not seem warranted for most locations. However, in regions experiencing strong oceanic influence or at high elevations, overall rainfall energy appears to be considerably lower than predicted by the general or USLE equations. Conversely, data collected at semi-arid to sub-humid locations suggest that rainfall energy may be higher than expected under those conditions. Standardised measurements are needed to evaluate rainfall intensity–kinetic energy relationships for such areas.

Modelling rainfall interception by vegetation of variable density using an adapted analytical model. Part 1. Model description.

The revised analytical model to predict rainfall interception by sparse canopies (Journal of Hydrology 170 (1995) 79) is further modified to improve the description of evaporation from wet vegetation whose canopy characteristics vary in time (e.g. agricultural crops, deciduous forest, fast-growing plantation forest, effects of storms, pests or logging, etc.). The main adjustments proposed are based on the following assumptions: (1) the canopy capacity is linearly related to leaf area index; (2) the evaporation rate from a saturated canopy can be expressed as an exponential function of leaf area index; and (3) evaporation from stems during the storms may be treated in a similar manner as that from the canopy. The comparative performance of the revised and the presently proposed version of the analytical model in predicting interception by a mixed cropping system in West Java, Indonesia is discussed in a companion paper (Part 2).

Modelling rainfall interception by vegetation of variable density using an adapted analytical model. Part 2. Model validation for a tropical upland mixed cropping system

Abstract To improve the description of rainfall partitioning by a vegetation canopy that changes in time a number of adaptations to the revised analytical model for rainfall interception by sparse canopies [J. Hydrol., 170 (1995) 79] was proposed in the first of two papers. The current paper presents an application of this adapted analytical model to simulate throughfall, stemflow and interception as measured in a mixed agricultural cropping system involving cassava, maize and rice during two seasons of growth and serial harvesting in upland West Java, Indonesia. Measured interception losses were 18 and 8% during the two measuring periods, while stemflow fractions were estimated at 2 and 4%, respectively. The main reasons for these discrepancies were differences in vegetation density and composition, as well as differences in the exposure of the two sites used in the two respective years. Functions describing the development of the leaf area index of each of the component crops in time were developed. Leaf area index (ranging between 0.7 and 3.8) was related to canopy cover fraction (0.41–0.94). Using average values and time series of the respective parameters, interception losses were modelled using both the revised analytical model and the presently adapted version. The results indicate that the proposed model adaptations substantially improve the performance of the analytical model and provide a more solid base for parameterisation of the analytical model in vegetation of variable density.

Improving Curve Number Based Storm Runoff Estimates Using Soil Moisture Proxies

Advances in data dissemination and the availability of new remote sensing datasets present both opportunities and challenges for hydrologists in improving flood forecasting systems. The current study investigates the improvement in SCS curve number (CN)-based storm runoff estimates obtained after inclusion of various soil moisture proxies based on additional data on precipitation, baseflow, and soil moisture. A dataset (1980-2007) comprising 186 Australian catchments (ranging from 51 to 1979 km 2 in size) was used. In order to investigate the value of a particular proxy, the observed S (potential maximum retention) was compared to values obtained with different soil moisture proxies using linear regression. An antecedent precipitation index (API) based on gauged precipitation using a decay parameter proved most valuable in improving storm runoff estimates, stressing the importance of high quality precipitation data. An antecedent baseflow index (ABFI) also performed well. Proxies based on remote sensing (TRMM and AMSR-E) gave promising results, particularly when considering the expected arrival of higher accuracy data from upcoming satellites. The five-day API performed poorly. The inclusion of soil moisture proxies resulted in mean modeled versus observed correlation coefficients around 0.75 for almost all proxies. The greatest improvement in runoff estimates was observed in drier catchments with low Enhanced Vegetation Index (EVI) and topographical slope (all intercorrelated parameters). The present results suggest the usefulness of incorporating remotely sensed proxies for soil moisture and catchment wetness in flood forecasting systems.

Reduction of infarct size by intravenous injection of uncultured adipose derived stromal cells in a rat model is dependent on the time point of application

Stem cell therapy is a promising tool to improve outcome after acute myocardial infarction (AMI), but needs to be optimized since results from clinical applications remain ambiguous. A potent source of stem cells is the stromal vascular fraction of adipose tissue (SVF), which contains high numbers of adipose derived stem cells (ASC). We hypothesized that: 1) intravenous injection can be used to apply stem cells to the heart. 2) Uncultured SVF cells are easier and safer when cultured ASCs. 3) Transplantation after the acute inflammation period of AMI is favorable over early injection. For this, AMI was induced in rats by 40min of coronary occlusion. One or seven days after AMI, rats were intravenously injected with vehicle, 5×10(6) uncultured rat SVF cells or 1×10(6) rat ASCs. Rats were analyzed 35 days after AMI. Intravenous delivery of both fresh SVF cells and cultured ASCs 7 days after AMI significantly reduced infarct size compared to vehicle. Similar numbers of stem cells were found in the heart, after treatment with fresh SVF cells and cultured ASCs. Importantly, no adverse effects were found after injection of SVF cells. Using cultured ASCs, however, 3 animals had shortness of breath, and one animal died during injection. In contrast to application at 7 days post AMI, injection of SVF cells 1 day post AMI resulted in a small but non-significant infarct reduction (p=0.35). Taken together, intravenous injection of uncultured SVF cells subsequent to the acute inflammation period, is a promising stem cell therapy for AMI.

Terrace erosion and sediment transport model: a new tool for soil conservation planning in bench-terraced steeplands

Abstract Despite widespread bench-terracing soil erosion remains a major problem in Java’s uplands. To elucidate the causes for this lack of impact, runoff and erosion processes were studied at a variety of spatial scales within a volcanic catchment in West Java. Research indicated that soil loss occurs via rain splash and wash of rainfall-detached sediment by shallow overland flow from the terrace riser and bed, and via runoff entrainment of sediment deposited in the central terrace toe drain. The terrace erosion and sediment transport mode (TEST) was developed to physically describe these processes, as a function of vegetation and soil surface cover where appropriate, yet use as few parameters as possible. Runoff generation was described by the spatially variable infiltration model (SVIM) and a two parameter rainfall depth-intensity distribution was assumed to derive a simple analytical expression for storm runoff depth. In a similar manner expressions were derived for effective rainfall kinetic energy to predict rainfall-driven transport using a newly developed model, and for effective runoff rate to predict flow-driven transport using GUEST model theory. The model and its components were tested using measured runoff and soil loss from 31 sections of terrace beds or risers and from six terrace units during two seasons. The model generally performed satisfactorily and provides a useful new tool for assessing the impacts of soil conservation measures on bench terrace runoff and soil loss.

Melodic cues for metre

A method of time-series analysis and a time-beating experiment were used to test the structural and perceptual validity of notated metre. Autocorrelation applied to the flow of melodic intervals between notes from thirty fragments of compositions for solo instruments by J S Bach strongly supported the validity of bar length specifications. Time-beating data, obtained with four stimuli from the same set, played in an expressionless mode, and presented under categorically distinct tempos to different subgroups of musically trained subjects, were rather inconsistent with respect to tapped bar lengths. However, taps were most frequently given to the events in the stimuli that corresponded with the first beats according to the score notations. No significant effects of tempo on tapping patterns were observed. The findings are discussed in comparison with other examinations of metre inference from musical compositions.

Conceptual evaluation of continental land-surface model behaviour

Continental land-surface models, such as the landscape component of the Australian Water Resources Assessment System (AWRA-L), aim to simulate the water balance over a wide variety of climates, land forms and land uses. To accommodate this range of hydrological conditions, model conceptualisation has to be flexible, while at the same time robust and parsimonious to allow for calibration using sparse data sets. In this study a Monte Carlo sensitivity analysis of the AWRA-L system is carried out as a step preceding calibration in which the hyperspace formed by parameters and initial conditions is explored using Latin Hypercube Sampling. The main goal is to test whether the model behaviour is in accordance with current understanding of Australian hydrology and to guide calibration. To visualise and analyse the high-dimensionality of the output space and the complex, non-linear interactions between processes and parameters, we used Self Organizing Maps, a non-parametric neural network. The results show that the main cause of non-linear model behaviour can be attributed to the ratio of rainfall over potential evaporation ratio, which determines which processes will dominate the water balance and the persistence of initial conditions. The model behaviour corresponds well to the current understanding of the hydrology of the Australian continent.

Understanding the global hydrological droughts of 2003?2016 and their relationships with teleconnections

Droughts often evolve gradually and cover large areas, and therefore, affect many people and activities. This motivates developing techniques to integrate different satellite observations, to cover large areas, and understand spatial and temporal variability of droughts. In this study, we apply probabilistic techniques to generate satellite derived meteorological, hydrological, and hydro-meteorological drought indices for the worlds 156 major river basins covering 2003-2016. The data includes Terrestrial Water Storage (TWS) estimates from the Gravity Recovery And Climate Experiment (GRACE) mission, along with soil moisture, precipitation, and evapotranspiration reanalysis. Different drought characteristics of trends, occurrences, areal-extent, and frequencies corresponding to 3-, 6-, 12-, and 24-month timescales are extracted from these indices. Drought evolution within selected basins of Africa, America, and Asia is interpreted. Canonical Correlation Analysis (CCA) is then applied to find the relationship between global hydro-meteorological droughts and satellite derived Sea Surface Temperature (SST) changes. This relationship is then used to extract regions, where droughts and teleconnections are strongly interrelated. Our numerical results indicate that the 3- to 6-month hydrological droughts occur more frequently than the other timescales. Longer memory of water storage changes (than water fluxes) has found to be the reason of detecting extended hydrological droughts in regions such as the Middle East and Northern Africa. Through CCA, we show that the El Niño Southern Oscillation (ENSO) has major impact on the magnitude and evolution of hydrological droughts in regions such as the northern parts of Asia and most parts of the Australian continent between 2006 and 2011, as well as droughts in the Amazon basin, South Asia, and North Africa between 2010 and 2012. The Indian ocean Dipole (IOD) and North Atlantic Oscillation (NAO) are found to have regional influence on the evolution of hydrological droughts.

Analysis of uncertainties in the inference of groundwater dynamics from gravity recovery and climate experiment observations over Australia

Groundwater management in Australia is complicated by the cost and scarcity (vs. spatial variability) of bore monitoring. Gravity Recovery and Climate Experiment (GRACE) remote sensing may alleviate this problem, but derived groundwater storage estimates are subject to errors, particularly, in total water storage (TWS) retrieval and in estimated soil moisture contributions to TWS. We quantified the uncertainties from both sources over Australia. In addition, for 12 regions we compared groundwater changes derived from GRACE with up-scaled groundwater bore measurements. Favourable agreement was found for regions with many bores, but a direct comparison was complicated by the scarcity and biased positioning of bores; uncertainty in soil moisture model assumptions; and uncertainty in the aquifer property that translates groundwater level into storage. Further improvements in spatial GRACE TWS resolution and in soil moisture estimation accuracy will be required to increase the utility of GRACE for groundwater management.